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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11DeepSeek released DeepSeek-V4.1-Flash-1017 on October 17, 2026, as an update to V4.1-Flash. The company reports a 77.0 score on DeepSWE v1.1, faster task completion and shorter outputs, while opening its Search & Fetch APIs to all users. The API model identifier remains deepseek-flash.
The update is available through DeepSeek’s website, app and API, with open-weight releases on Hugging Face and ModelScope. Search and Fetch calls cost $0.75 per 1,000 calls once billing begins, although server-side calls made through supported coding-agent tools remain free for DeepSeek API users until October 31, 2026, at 16:00 UTC.
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What changed in DeepSeek V4.1-Flash-1017
The October 17 release updates the existing V4.1-Flash model rather than introducing a new API name. DeepSeek says the revision improves benchmark performance, completes tasks faster and produces shorter outputs. The website, mobile app and API were updated at launch, but applications calling the API should continue using deepseek-flash.
DeepSeek also removed the previous access restriction on its Search & Fetch tools. Any developer using the API can now build workflows that search the current web or retrieve source content, subject to the call pricing and temporary free-use policy described below.
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How strong is the reported 77.0 DeepSWE result?
DeepSeek’s change log reports 77.0 on DeepSWE v1.1. That number is a benchmark result, not a general accuracy percentage or a guarantee that every coding task will succeed. The company evaluated DeepSWE with the Mini-SWE-V2 framework, so comparisons are meaningful only when another result uses the same benchmark version and evaluation setup.
| Benchmark | Reported score | Important condition |
|---|---|---|
| DeepSWE v1.1 | 77.0 | Mini-SWE-V2 framework |
| HLE | 42.6 | Without tools; 44.0 on the marked pure-text subset |
| Terminal-Bench 4.0 | 42.3 | Claude Code framework |
| ProgramBench | 29.1 | Condition not stated in the release notes |
| NL2Repo-Bench | 68.2 | Condition not stated in the release notes |
| Automation-Bench v1.0.6 | 60.5 | Condition not stated in the release notes |
| Agents’ Last Exam | 35.4 | Condition not stated in the release notes |
| Apex Bench v1.1 | 72.1 | Condition not stated in the release notes |
| Chartography | 83.0 | With tools |
| BabyVision | 92.5 | With tools |
| ZeroBench-main | 51.0 | With tools, measured as Pass@5 |
The HLE figure labeled “marked subset” uses only the pure-text portion of that evaluation. Terminal-Bench 4.0 was run through the Claude Code framework, while ZeroBench-main uses Pass@5, meaning the reported value reflects the chance of at least one success across five attempts rather than a single deterministic run. Those details matter when reading the table: tool access, framework behavior and the number of attempts can materially change a score.
Model architecture and capability
The September V4.1-Flash release describes a 552-billion-parameter mixture-of-experts model with a new causal encoder-decoder architecture. It activates approximately 8 billion parameters for input processing and 16 billion for output generation, rather than using all 552 billion parameters on every token. The model also supports native visual understanding, so coding-agent workflows can include images and other visual inputs without a separate vision model.
DeepSeek says its newer key-value cache requires one quarter of the HBM and one eighth of the SSD storage used by the previous generation. These are company-reported architecture claims, not independent measurements, and actual memory use depends on context length, batching, quantization and deployment software.
Search & Fetch API: access, endpoint and price
The documented search endpoint is https://api.deepseek.com/v1/tools/search. Use Search when an agent needs current web information and Fetch when it needs the contents of a discovered source. This makes the model more suitable for research, monitoring and coding tasks that depend on information newer than the model’s training data.
DeepSeek says its in-house search engine handles hundreds of millions of requests daily. The published rate is $0.75 per 1,000 Search or Fetch calls. The price applies per endpoint call, so a workflow that performs one search and then fetches two pages uses three billable calls once charging starts.
| Period | Who is covered | Price |
|---|---|---|
| Through October 31, 2026, 16:00 UTC | Server-side Search & Fetch calls made through DeepSeek Harness, Claude Code or Codex by DeepSeek API users | Free |
| Beginning October 31, 2026, 16:00 UTC | Search and Fetch endpoint calls | $0.75 per 1,000 calls |
“Search & Fetch calls via server-side tools in DeepSeek Harness, Claude Code, and Codex are currently free for DeepSeek API users.” — DeepSeek API Docs, October 17, 2026.
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The free policy is specifically for those server-side tool paths. It should not be interpreted as a permanent waiver for every direct API integration; developers should track calls and review the account’s billing behavior before the October 31 cutoff.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Can coding agents use V4.1-Flash-1017?
Yes. DeepSeek says the model is optimized for DeepSeek Harness, Tencent CodeBuddy and WorkBuddy, and related coding-agent environments. The English release page also lists OpenCode as a supported partner. DeepSeek’s free server-side Search & Fetch announcement additionally names Claude Code and Codex.
- Keep the API model value as
deepseek-flash; the release did not publish a new model identifier for the 1017 update. - Use the agent framework’s native tool integration when you want the temporary free server-side Search & Fetch path.
- Record which benchmark harness, tool permissions and retry policy your agent uses, because those settings affect both results and cost.
- Budget for Search and Fetch calls after October 31, 2026, even if the surrounding coding-agent subscription or software is free.
Availability and deployment options
Individuals can access the update through DeepSeek’s website and app or call it through the API. Developers who need local control can obtain the open-weight distribution through Hugging Face and ModelScope. Local deployment still requires hardware sized for the selected weights, context length, quantization and serving stack; the 552B total parameter count should not be treated as a statement that every deployment needs to load all parameters simultaneously.
For large production installations, DeepSeek invites organizations planning deployments with 2,000 GPUs plus a storage cluster to contact the company. That invitation points to an enterprise infrastructure path rather than a requirement for ordinary API or app users.
What the release means in practice
The most consequential change is the combination of stronger coding-agent benchmark results and built-in access to current web sources. A team can use the same model for repository edits, terminal work, visual inputs and source retrieval instead of stitching together separate services. The trade-off is operational: benchmark scores depend on their harnesses, the Search & Fetch price becomes usage-based after the free period, and the model’s memory claims are vendor estimates rather than independent capacity tests.
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